Analytics Trends 2018: Blockchain and AI to Accelerate Clinical Trials Transformation

With more than 60% of clinical trials exceeding their planned timelines and budgets, pharmaceutical industry, patients, and regulatory agencies are looking for transformational changes in the conduct and operational effectiveness of clinical trials to bring drugs sooner to the markets.

Over the last few years, digital technologies and insights gleaned from Real World Data (RWD) have offered several avenues for improving clinical trials, but their realization and adoption has been sketchy at best for various reasons. However, recent advancements and extreme innovation in data management and analytics methodologies are turning some of these promises into reality.

Let’s review three key areas of promise that are poised to bring transformative changes to both the planning and conduct of clinical trials in 2018 and beyond.

1. Blockchain for Clinical Trials Data: As a secure, public, and decentralized data-store, blockchain technology offers, by far, the most promising opportunity to solve many entrenched problems around data management for the conduct of clinical trials. The inherent Smart Contracts within blockchain allows multiple stakeholders to transact and bind into digital contracts[1]. It is a huge opportunity not only for data integrity and process validity but also for reduction of cost elements in several manual clinical trial processes. Sponsor and regulatory reviews of data shared by clinical trial ecosystem consequently get a new paradigm. The trust-deficit in implementation and adoption of “Risk Based Monitoring” (RBM) programs gets reduced, giving further cost and time advantages. Blockchain will ensure the inviolability and historicity of clinical trial data, thereby safeguarding the data integrity of analysis. Several exciting downstream opportunities for collaboration and sharing of trusted data and insights will open up as a result.

2. Collaborative Sharing of Insights: Patients recruited for clinical trials represent only a small fraction of the medical variability in the real world. This is why the concept of RWD and medical outcomes are critical. Currently, for many innovative first-in-class drugs and treatments, real world data is unlikely to be easily available. Pharmaceutical and biotech companies are actively exploring methods for pre-competitive sharing of clinical data. The ability to share and attribution of anonymized raw clinical data, along with timestamped insights generated from each analysis gets a major boost by applying recent technology advancements. In an earlier post [2], we referred to such rich collaborative data as “Analytics Elements” being shared.

The basic premise of an Analytics Element is that at any given time, the available data sets and certain algorithms applied to them gives unique insight. Let’s imagine a scenario where these Analytics Elements get shared across a blockchain of clinical trials, where secured data resides encrypted in their respective repositories, and only de-identified aggregated results are returned and shared across the nodes.

MIT’s Project Enigma[3] represents a big promise of this paradigm of ‘move algorithm to data’. A secured data infrastructure with tools to create and share these insights across patients, pharmaceutical companies, providers, payers, CROs, and other ecosystem providers is now possible at low costs. Multiple stakeholders across study planning, conduct, and regulatory reporting processes get unprecedented operational advantage from these insights while maintaining data privacy, integrity, and their competitive differentiation.

3. OMICS and AI: The entire process of patient identification, selection, recruitment, and nurturing remains as one of the key problems to solve. However, omics patient data from genomics, proteomics, and metabolomics, along with advances in artificial intelligence models for augmenting recruitment data, provides great progress for building better recruitment models. We expect that the traditional inclusion and exclusion approaches will get a huge boost in 2018.

Additionally, a wealth of data will be available about Single Nucleotide Polymorphisms (SNP’s), Choroidal Neovascularization (CNV’s) and their influence on patient outcomes, like drug metabolism and response to drugs. Only patients that fit a given omic profile will need to be recruited, potentially de-risking a clinical trial significantly.

Pharmaceutical and CRO industries will leapfrog clinical trial conduct by more than a generation, as patient recruitment probabilities, site readiness, principal investigator access, and other operational aspects, will get unprecedented support from technology.

All in all, clinical trials are set to get a much-needed boost for improved planning, conduct, reporting, and collaborative sharing of valuable insights. 2018 is going to be an exciting year where we will see some of these rapid advances and technology adoptions finally enabling transformative changes to the ways in which pharmaceutical organizations can bring highly innovative products to market faster and at lower costs.

References:
1) Blockchain technology for improving clinical research quality
2) Analytics Elements to Establish Semantic Consistency in Data Lakes
3) OPAL/ENIGMA, MIT: Blockchain & Health IT

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About Sagar Anisingaraju

mmAs Saama’s Chief Strategy Officer, Sagar Anisingaraju creates strategic initiatives that lead Saama into emerging business areas with competitive differentiation. He enjoys his time spent with customers to understand their unique data assets and to help them generate business outcomes from them. Sagar is also instrumental in creating an experimental culture and setting up innovation.ai programs across pharmaceutical clients of Saama. He won Innovation Enterprise’s Chief Strategy Officer of The Year award in 2013.


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